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Voice risk analysis

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Last updated 17th October 2019.

Voice risk analysis (“lie detector” or “VRA”) technology is sometimes used in telephone calls on insurance claims, and by some local authorities. VRA aims to spot people who are more likely to be giving false information. This may unfairly disadvantage people who stammer.

About voice risk analysis

Details may vary, but the following is summarised from Disability Alliance Factsheet: Voice risk analysis and benefit claims (archive of disabilityalliance.org, 2011):
Voice risk analysis flashes up on a screen whether answers given by a caller are HR (‘high risk’, ie. more likely to be false) or LR (‘low risk’). At the start of an interview the software is ‘calibrated’ by asking basic questions such as name, address and date of birth. This is taken as ‘normal, and the software looks at changes in voice patterns when further questions are asked, such as any hesitation or unwillingness to answer a question. Depending on readings from the software, the claim can be either fast-tracked or subjected to more rigorous scrutiny. The questioner can override HR messages to prevent false readings, for example if someone is hard of hearing and hesitates.

Equality Act implications and stammering

People who stammer may be flagged up as high risk because of hesitations, backtrackings or other features produced by the stammer, or any result of the software may simply be unreliable because it is not geared to stammering: see below Problems using VRA with stammering. There is an article on the British Stammering Association website: Worries over voice risk analysis to combat crime (stamma.org), from summer 2006.

Detriments to the person who stammers from being flagged as high risk will depend on the circumstances, but may include:

  • being subjected to extra questioning (which a person who stammers may find particularly difficult on the phone) or perhaps to other checks,
  • perhaps delay in receiving a payment to which the person is entitled (or not receiving it?),
  • depending on the system, perhaps it being on the person’s record that they were flagged as high risk even though they were later found to be honest; and
  • potentially the offensive stigmatising nature (see CHEZ) of being put though extra checks because of the stammer.

If the service provider or public body is aware of the stammer (for example if the customer is obviously having some struggles to speak), they may need to discount any negative results from VRA. Failure to do so may be contrary to s.15 EqA as discrimination arising from disability, on the basis that the person who stammers would otherwise be treated unfavourably without sufficient justification. The software’s results will (presumably) not be useful in such cases, so that discrimination is unjustified. There is also potential Equality Act liability under s.15 even if the service provider does not know of the stammer, if it fails to show that it could not reasonably have been expected to know of the disability.

This is all well and good if (a) interviewers are told to disregard HR results from stammering and (b) the interviewer realises the person has a stammer and does indeed follow the instructions. I do not know what, if any, instructions interviewers are given about stammering. Even if the instructions are given and followed, an important point is that the interviewer may not realise the person has a stammer. Assuming use of VRA is justified in the first place, it may be an obligation under the Equality Act to adequately train interviewers to recognise (so far as possible) a person who has a stammer or other communication impairment. However a person who stammers will often try and hide it as far as possible. The stammer may be having effects on speech which are not clearly stammering: see below Problems using voice risk analysis with stammering.

The service provider might consider whether to ask a caller if they have a speech impairment which might affect the VRA. This raises various issues however, for example: a significant number of people who have a stammer may be reluctant to say so; is it consistent with Article 9 GDPR on health data (eg is consent for processing given “freely” in these circumstances?); and a fraudulent caller potentially answering “yes” when they don’t have an impairment.

Even where the service provider or public body does not know of the stammer and cannot reasonably be expected to know of it, there is potential Equality Act liability for indirect discrimination and failure to make reasonable adjustments. In the case of service providers and bodies exercising public functions, there is no explicit defence here as regards not knowing about the disability (see Reasonable adjustments by service providers>Knowledge of disability and Knowledge of disability>Indirect discrimination – is knowledge required?). In looking at whether indirect discrimination against people with speech impairments is justified, one issue will be whether the service provider or public body can show there is sufficient evidence that VRA is effective in reducing fraud generally.

Insurance claims

Some (perhaps many) insurance companies use voice risk analysis software on people phoning up to make claims, to flag up any that are likely to be dishonest. Claims flagged up by the software can then be subject to particularly rigorous investigation. See Worries over voice risk analysis to combat crime (stamma.org), summer 2006. As outlined above, these arrangements may breach the Equality Act.

Benefit claims

Voice risk analysis was piloted for welfare benefit claims from 2007. Representations were made to the Department for Work Pensions (DWP) about the problems of using the software with disabled claimants. As a result of the trials, in autumn 2010 the DWP abandoned plans to introduce VRA for welfare benefits, saying it was not good value for money. However it was reported in 2014 (link below) that some local authorities were still using VRA, or considering doing so. Links:

Use of voice recognition technology for welfare benefits may breach Equality Act rules on public functions unless there are appropriate safeguards for stammering and other communication impairments. Its use may also involve a breach of the public sector equality duty (PSED) unless stammering and other communication disabilities are properly considered.

Problems using voice risk analysis with stammering

  • ‘Basic’ questions such as name and address are often a particular struggle for someone who stammers. Yet these basic questions are apparently used to ‘calibrate’ the software to the interviewee’s ‘normal’ pitch and tone, enabling it to detect any change on the later more probing questions. Where a person struggles on those basic questions, one would not expect the software to give any useful results.
  • Alternatively, the normal hesitations, repetitions and other features of stammering (including hidden effects outlined below) may trigger the software.
  • The fact that the person will be notified when their speech is going to be analysed by a lie detector may serve to increase stress levels and dysfluency, which may make them more likely to be suspected of fraud.
  • Apparently the interviewer has the power to override HR messages to prevent false readings, e.g. if someone is hard of hearing and hesitates. However, a key feature of stammering is that the person often tries to hide the fact that they stammer. The interviewer may well not realise that they have a stammer. The interviewer may just hear hesitations, backtracking, filler phrases such as “well”, “you see” or other results of the person trying to hide the stammer. These may be interpreted by the software as HR (high risk).
  • Presumably the software has not been tested – and therefore not validated – with stammering.
    Also different people stammer differently.
  • See also Mistaking stammering for dishonesty (in context of court appearances).

For issues of using VRA where a person has a disability more generally, see archived Disability Alliance Factsheet: Voice risk analysis and benefit claims (archive of disabilityalliance.org), 2011

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